A workflow in snakemake to classify taxomomic levels of metagenomic Illumina 16S rRNA (V4 region) data derived from horse gut microbiome.
- snakemake version 6.1.0
- sra toolkit version 2.11.0
- Instructions for installation (don't forget to replace current with 2.11.0)
- qiime2 version 2021.2
- R version 4.0.3
- ggplot2 version 3.3.3
- stringr version 1.4.0
If you want to use this workflow, download and extract this repository and install the requirements.
Configure the workflow according to your needs via editing the file config.yaml
The file looks like this:
data_location: "data/"
output_location: "output/"
log_location: "logs/"
denoising_params:
trunc-len-f: 150
trunc-len-r: 150
trim-left-f: 13
trim-left-r: 13
trunc-q: 0
chimera-method: 'pooled'
pooling-method: 'pseudo'
barplot_params:
taxonomic_level: "Phylum"
percentage_present_in_sample: 0.5
filename: "barplot.jpg"
width: 600
height: 600
filter: "Kingdom=Bacteria"
The data_location is the location where the data files that are needed for this workflow are stored. The path to this directory is relative to where the workflow is executed In this folder there should be three files:
- SRR_Acc_List.txt
- SraRunTable.txt
- classifier.qza
SRR_Acc_List.txt and SraRunTable.txt can be downloaded from the NCBI SRA run selector. The ones used in the example on this repository can be found here.
The classifier is a Qiime2 artifact, the one used in this workflow is the Greengenes 13_8 99% OTUs from 515F/806R region of sequences trained by Qiime2, it can be downloaded here
The output_location is the folder where the generated data and visualizations are stored. The path to this directory is relative to where the workflow is executed
The log_location is the folder where the logs generated by this workflow will be stored. The path to this directory is relative to where the workflow is executed
The denoising_params are the parameters used for the qiime dada2 denoise-paired that is executed in this workflow. For more information on these parameters go to Qiime2 documentation
The barplot_params are the parameters that are given to the R script that will generate the final barplot visualization of this workflow.
The taxonomic_level is the taxonomic level that will be shown in the barplot. E.g. if the taxonomic level is set to "Phylum" the different phyla represented in the data will be shown in different colors in the barplot.
The percentage_present_in_sample is the minimum percentage a taxonomic unit has to be present in one of the samples at any one timepoint or treatment method to be shown in the barplot.
The filename is self explanatory, this is the filename to which the barplot will be saved to. The file will be found in the output folder.
The width and height are the width and height in pixels that the barplot will be saved at.
The filter should always be in the format {taxonomic_level={taxonomic_unit}}. The data that will be displayed in the plot will only be that is assigned to the taxonomic unit in this filter parameter.
Navigate to the correct folder via the command line. Folders WC-02 to WC-05 contain the assignments done for the tutorials from weeks 2 to 5. The folder called final contains the final assignment (the horse gut workflow). Each of these folders contain a snakefile that can be run by executing
snakemake --cores $N
Where $N is the number of cores you want to use.
When executing the final workflow it is advised to first run
snakemake --cores $N quality_check_qiime
This will download the SRA files with the accession number in the SRR_Acc_List.txt, make a Qiime2 artifact with these files (called paired-end-demux.qza, found in output/qiime_artifact). And make a visualization of the quality of the reads. This visualization is stored in output/quality_check/visualization.qzv. This is an archive with a folder called data, this folder has a file called index.html. Going to this file in yout browser you get an overview of the quality of the reads in your data. If you click on the tab Interactive Quality Plot you can see two interactive plots. On the left hand side an interactive plot that shows the quality of the forward reads and on the right hand side a plot the quality of the reversed reads. Based on the information on this page you can adjust the denoising_params parameters in the configuration file. When adjusting the trunc-len-f and trunc-len-r parameters please keep in mind that the reads still need to overlap at with least 12 basepairs to continue with the rest of the workflow.
After adjusting the denoising_params to your needs you can go ahead and execute the rest of the workflow by running the following command
snakemake --cores $N
Running this will give you the end product of the workflow, a barplot with the taxonomic classification of the sequences in your data. An example is given below.
If running the workflow results in an error while making the barplot, please check the output/denoising/denoising-stats.qza archive. In this archive you will find a data folder with a stats.tsv file. Here you can check how many reads were filtered out by the denoising step. If there are too little reads left this might result in problems in the rest of the workflow. If this is the case readjust the denoising_params and try to run the workflow again.
Naomi Hindriks
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